Multimodal Technologies and Interaction

24 pages, 2636 KiB

Open AccessArticle

Improving User Experience and Communication of Digitally Enhanced Advanced Services (DEAS) Offers in Manufacturing Sector

by Mohammed Soheeb Khan, Vassilis Charissis, Phil Godsiff, Zena Wood, Jannat F. Falah, Salsabeel F. M. Alfalah and David K. Harrison

Multimodal Technol. Interact. 2022, 6(3), 21; https://doi.org/10.3390/mti6030021 - 16 Mar 2022

Cited by 7 | Viewed by 3679

Abstract

Digitally enhanced advanced services (DEAS), offered currently by various industries, could be a challenging concept to comprehend for potential clients. This could result in limited interest in adopting (DEAS) or even understanding its true value with significant financial implications for the providers. Innovative ways to present and simplify complex information are provided by serious games and gamification, which simplify and engage users with intricate information in an enjoyable manner. Despite the use of serious games and gamification in other areas, only a few examples have been documented to convey servitization offers. This research explores the design and development of a serious game for the Howden Group, a real-world industry partner aiming to simplify and convey existing service agreement packages. The system was developed under the consultation of a focus group comprising five members of the industrial partner. The final system was evaluated by 30 participants from engineering and servitization disciplines who volunteered to test online the proposed system and discuss their user experience (UX) and future application requirements. The analysis of users’ feedback presented encouraging results, with 90% confirming that they understood the DEAS concept and offers. To conclude, the paper presents a tentative plan for future work which will address the issues highlighted by users’ feedback and enhance the positive aspects of similar applications. Full article

(This article belongs to the Special Issue Feature Papers of MTI in 2021)

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15 pages, 1098 KiB

Open AccessArticle

Adolescents’ Vulnerability to Fake News and to Racial Hoaxes: A Qualitative Analysis on Italian Sample

by Concetta Papapicco, Isabella Lamanna and Francesca D’Errico

Multimodal Technol. Interact. 2022, 6(3), 20; https://doi.org/10.3390/mti6030020 - 4 Mar 2022

Cited by 28 | Viewed by 11688

Abstract

Following the Digital Revolution, we are witnessing an increase in the number of manipulated sources of information. For this reason, virtual environments can be a breeding ground for the proliferation of prejudices and stereotypes, resulting from the spread of racial fallacious news, known as ‘racial hoaxes’. Adolescents may be more susceptible due to the tense and complicated relationship between their experience with digital platforms and the development of their relatively limited critical thinking. In this landscape, in order to explore the features of disinformation in adolescence, the research involved 41 Italian adolescents between 13 and 16 years old, balanced by gender and school education. The teenagers took part in the focus group discussions on the topic of online information preferences, fake news and racial hoaxes, which were analyzed by means of content analysis. The answers given by participants show a so-called adolescents’ perception of ‘misinformation invulnerability’ that can influence their credulity in fake news, since they are aware of fake news but they are not so able to recognize or remember it. Full article

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18 pages, 1280 KiB

Open AccessArticle

Videogame-Based Training: The Impact and Interaction of Videogame Characteristics on Learning Outcomes

by Diana R. Sanchez

Multimodal Technol. Interact. 2022, 6(3), 19; https://doi.org/10.3390/mti6030019 - 1 Mar 2022

Cited by 3 | Viewed by 3734

Abstract

Virtualized training provides high fidelity environments to practice skills and gain knowledge, potentially mitigating harmful consequences from real life mistakes. Current research has focused on videogames, believed to have characteristics that improve learning. There is conflicting evidence on the benefits of using videogame-based training to improve learning. This study explored the impact of two videogame characteristics (i.e., rules/goals clarity and human interaction), on mid-training scores and post-training scores (i.e., familiar task and novel task). Results from a sample of 513 undergraduates showed that both videogame characteristics significantly impacted mid-training performance but not post-training performance; clear rules/goals and completing the training alone improved mid-training performance. There was also a significant moderation between the two videogame characteristics for post-training scores on the novel task, but not the familiar task, or mid-training performance. Findings suggest videogame characteristics have an immediate but not sustained impact on learning; implications are discussed. Full article

(This article belongs to the Special Issue Innovations in Game-Based Learning)

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29 pages, 26599 KiB

Open AccessArticle

Detecting Groups and Estimating F-Formations for Social Human–Robot Interactions

by Sai Krishna Pathi, Andrey Kiselev and Amy Loutfi

Multimodal Technol. Interact. 2022, 6(3), 18; https://doi.org/10.3390/mti6030018 - 23 Feb 2022

Cited by 8 | Viewed by 4025

Abstract

The ability of a robot to detect and join groups of people is of increasing importance in social contexts, and for the collaboration between teams of humans and robots. In this paper, we propose a framework, autonomous group interactions for robots (AGIR), that endows a robot with the ability to detect such groups while following the principles of F-formations. Using on-board sensors, this method accounts for a wide spectrum of different robot systems, ranging from autonomous service robots to telepresence robots. The presented framework detects individuals, estimates their position and orientation, detects groups, determines their F-formations, and is able to suggest a position for the robot to enter the social group. For evaluation, two simulation scenes were developed based on the standard real-world datasets. The 1st scene is built with 20 virtual agents (VAs) interacting in 7 different groups of varying sizes and 3 different formations. The 2nd scene is built with 36 VAs, positioned in 13 different groups of varying sizes and 6 different formations. A model of a Pepper robot is used in both simulated scenes in randomly generated different positions. The ability for the robot to estimate orientation, detect groups, and estimate F-formations at various locations is used to determine the validation of the approaches. The obtained results show a high accuracy within each of the simulated scenarios and demonstrates that the framework is able to work from an egocentric view with a robot in real time. Full article

(This article belongs to the Special Issue Feature Papers of MTI in 2021)

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Multimodal Technol. Interact., Volume 6, Issue 3 (March 2022) – 4 articles

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